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cs.AI2026
Rectification Difficulty and Optimal Sample Allocation in LLM-Augmented Surveys
Zikun Ye, Hema Yoganarasimhan
Large Language Models can generate synthetic survey responses at low cost, but their accuracy varies unpredictably across questions. We study the design problem of allocating a fix…
cs.AI2025
TextBO: Bayesian Optimization in Language Space for Eval-Efficient Self-Improving AI
Enoch Hyunwook Kang, Hema Yoganarasimhan
Large Language Models (LLMs) have enabled self-improving AI systems that iteratively generate, evaluate, and refine their outcomes. Recent studies show that prompt-optimization-bas…